Naomi Pinto

Built a RAG-based internal knowledge system that ingests wiki, chat, and email to resolve support queries without human escalation, reducing load on engineering and ops. Drove ~90% automation of rebalancing by restructuring system logic and decision flows, and partnered with architects to define constraints, data flows, and operational health for safety-critical workflows.

Owned and redesigned enrollment and activation systems for 15M+ users, improving activation by 28% and engagement by 9.5% through behavioral sequencing and decision-path design. Built agent-assisted chat and conversational flows to reduce friction at high-dropout moments, and established experimentation loops and behavioral analytics to make user decision patterns legible across the funnel.

Managed $15B pension platform operations while redesigning reporting and analytics workflows, cutting performance reporting from ~2 months to ~2 hours via data pipeline automation. Built internal dashboards and tooling that reduced manual coordination and improved operational transparency across a complex institutional platform.

Led online trading experience for ~5M users during early consumer fintech formation, launching personalized alerts and dashboard systems that shaped UX patterns still used today. Applied product judgment in the absence of established playbooks, focusing on user workflow effectiveness and engagement.

Completed 'Large Language Models for Business with Python' through Stanford Continuing Studies in 2025.

Completed an MBA in Finance & Investment Management at USC Marshall School of Business.

Earned a Bachelor of Arts in Economics & English Literature from Johns Hopkins University.

Completed 'Design for Play: Turning Ideas into Meaningful Action' through Stanford Continuing Studies in 2025.

Completed continuing education at Johns Hopkins University (program details not specified).